A Novel Learning-Based Binarization Scheme Selector for Swarm Algorithms Solving Combinatorial Problems

A Novel Learning-Based Binarization Scheme Selector for Swarm Algorithms Solving Combinatorial Problems

Currently, industry is undergoing an exponential increase in binary-based combinatorial problems. In this regard, metaheuristics have been a common trend in the field in order to design approaches to successfully solve them. Thus, a well-known strategy includes the employment of continuous swarm-bas...

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Bibliographic Details
Main Authors: José Lemus-Romani, Marcelo Becerra-Rozas, Broderick Crawford, Ricardo Soto, Felipe Cisternas-Caneo, Emanuel Vega, Mauricio Castillo, Diego Tapia, Gino Astorga, Wenceslao Palma, Carlos Castro, José García
Format: article
Language:EN
Published: MDPI AG 2021
Subjects:
combinatorial problems
metaheuristics
binarization scheme
SARSA
Q-learning
machine learning
Mathematics
QA1-939
Online Access:https://doaj.org/article/8ca18ce3021a4d73bff5c1776622d0a9
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https://doaj.org/article/8ca18ce3021a4d73bff5c1776622d0a9

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